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© 2015 IBM Corporation

Predictive Customer Intelligence

Sogeti 2015

Damiaan Zwietering

[email protected]

© 2015 IBM Corporation2

Trade with meSharing data, location, and new ideas in return for better products and value

Educate meBringing expertise to every customer interaction

Let me chooseOptions vs. prerequisites, roadmaps vs. checkboxes

Grow with meData and insight connecting the lives of customers, households

Find meUsing visualization and analytics to discover new customer segments

Ask meConsulting customers on products, services, and social issues

Know meOffer new products and services based on understanding my wants, needs

Excite meUnexpected services at unexpected moments

2

Customer expectations are driving companies towards being customer centric


Organizational capabilities have been a hindrance to customer centricity

Inability to gather and synthesize insights to customer behavior, needs and preferences from analysis of multiple data sources

Difficult to deliver omni-channel customer analytics solution able to analyze, score and determine most appropriate action with individual customer

Only historical view of customer, resulting in inappropriate or incomplete offers or communications at the time of interaction

Challenged in using analytics to add short-term value or enhance long-term strategy

Lack of channel integration and siloed lines of business, causing inconsistent or tactical customer interactions

Inconsistent service delivery and weak customer relationships, resulting in low retention

Focus on uncoordinated marketing offers - one-hit selling, as opposed to lifetime value


Chat

Voice

Email

Social media

Interactive voice response

Mobile

Short Message Service

Web

Acquisition models

Campaign response models

Churn models

Customer lifetime value

Price sensitivity

Product affinity models

Segmentation models

Sentiment models

Up-sell / Cross-sell models

Campaigns

Offers

Messaging

Lead management

Cross channel campaign management

Real time marketing

Marketing event detection

Digital marketing

Customer services

The optimized customer insight and engagement process

Data Predictive customer insightReal time or historical

Enterprise marketing

Multi-channel customer interactions


Organizations can Acquire, Grow and Retain customers by harnessing all customer data to improve customer interactions and relationships

ACQUISITION

RETENTION

PERSONALIZATION

GROWTH

5


Predictive Customer Intelligence key capabilities

ANALYZE data to gain critical insights

DEPLOY to real-time channels for point-of-impact action

ACCELERATE time to value with focused solutions


Many, many rich modeling techniques

Social Network Analysis

DemographicSegmentation

Churn Modeling, Next Best Offer

Real-time Decision

Management

Campaign Management

Customer Value Calculation

Loyalty Segmentation


① An activity occurs that calls for a decision.

② The context from the activity is passed to the decision process.

③ The decision process augments the context with stored information and runs the decision model.

④ One or more actions are recommended to the activity.

⑤ The activity feeds back the results to help tune the model over time.

Real-time decision loop allows predictive models to get even smarter

Context

Action

Decision

Activity

Feedback

Information

Facts,recent events,

options

Decision input, actions and outcomes

3

5

3

2

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Built-in Connectors provide enhanced functionalities

InfoSphere Streams Quickly ingest, analyze and correlate large data sets from real-time sources and interact with individual customers at scale.

IBM Interact Allow the power of the deep algorithms to be introduced at the moment of impact, including the inclusion of contextual data

IBM Customer Intelligence Optimizer, Lifetime Value Maximizer

Optimize customer-specific actions/ offers to maximize long term customer value by moving customers to a “higher value state”

IBM BigInsights (and other Hadoop Distribution)

Pull together large volumes of all different types of data including social/unstructured information and structured data like transaction details for enhanced discovery


Industry accelerators


Online quote

(Adapted)

Terms & Conditions fine print

Advice from Agent

Policy paperwork

FirstPayment

AmendPolicy

First Claim

ComplaintResponse

Cross-sellCampaignBilling

dept.

Second payment

Marketing

Comparison website

Product development

Intermediary

Underwriting

Finance

Policy admin

Claims management

Marketing

Customer Service


Customer Track(Nature of

Interactions)

AcquisitionChannel

Quality of ClaimExperience

Quality of Service Experience

Renewal Rate

Low

Very High

High

Medium

Percentage of customers Renewal rate

Phone

55% 72%

Claim only

6% 81%

Claim & Service

6% 72%

Service only

34% 66%

No Contact

54% 72%

PositiveExperience

32% 82%

NeutralExperience

55% 75%

NegativeExperience

13% 60%

Aggregator

50%23%

Web

22% 55%

PositiveExperience

NeutralExperience

NegativeExperience

PositiveExperience

NeutralExperience

NegativeExperience

PositiveExperience

NeutralExperience

NegativeExperience


Recommended Action:Service Offer

“Get ready for summer with a free airco check”

Recommended Action:Targeted Retention Offer

“10% discount with 2 year fixed price guarantee and lower deductible”


“10% discount and lower deductible”


“10% discount with 2 year fixed price guarantee”

Likelihood of Cancellation

Loss Ratio Prediction

The retention offer decision depends on the combination of

these three factors:Future Lifetime Value


Predictive Customer Intelligence Architecture Overview

PureData for Analytics

Deep customer analytics

Actionable customer data

Big InsightsExplore new

customer insights from all data

MDMTrusted

customer data

Predictive Modeling

and Optimization

Reporting

Real-time Scoring

Data Repository for

Real Time Analytics

WA

S / IB

M In

tegra

tion

Bu

s

Uns

tru

ctur

ed •

S

truc

ture

d

Data Sources Points of Interaction

Direct Mail

Email

Chat

Call Center

Mobile Apps

Web

Social

Chat

Call Center

Mobile Apps

Web

TransactionalData

Model Repository(Industry-specific)

SegmentationModel

Sentiment Analysis

Churn Model

Up-sell / Cross-sell Model

AcquisitionModel

Campaign Response

Model

Lifetime Value MaximizerModel (GBS)

IBM Predictive Customer Intelligence

Inbou

nd In

teraction

sO

utbound

Inte ractions

GBS Lifetime Value MaximizerCustomer Lifetime Value & Segment

Migration

3rd pa

rty m

arke

ting

applica

tion

Cam

paig

n • I n

terac

t M

arketing exec utio

n &

recomm

enda

ti on eng

ine

External data- social, blog

CustomerDemographic Data

CustomerInteraction History

SMS

SMS

SMS


Behavior-Based Customer Insight Solution for Insurance

Integration into Marketing & Distribution Dashboards

Behavior-based Segmentation Analysis

• Generates advanced segmentation and individual insight based on behavior

• Identifies key target customers to retain

• Proactively identify "at-risk" customers early

• Enables channels to act

Behavior-based

Segmentation Segmentation Analysis drill-

down

Retention Monitor

Retention Reports


The IBM difference

ibm predictive customer intelligence - sogeti.nl customer... · predictive customer intelligence...

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